Authors: Knott, M.¹; Tzamourani, P.²

Source: British Journal of Mathematical and Statistical Psychology, Volume 60, Number 1, May 2007 , pp. 175-191(17)

Abstract:

This paper focuses on the two-parameter latent trait model for binary data. Although the prior distribution of the latent variable is usually assumed to be a standard normal distribution, that prior distribution can be estimated from the data as a discrete distribution using a combination of EM algorithms and other optimization methods. We assess with what precision we can estimate the prior from the data, using simulations and bootstrapping. A novel calibration method is given to check that near optimality is achieved for the bootstrap estimates. We find that there is sufficient information on the prior distribution to be informative, and that the bootstrap method is reliable. We illustrate the bootstrap method for two sets of real data.

Document Type: Research article

DOI: 10.1348/000711006X107539

Affiliations: 1: Department of Statistics, London School of Economics and Political Science, UK 2: Department of Statistics, Bank of Greece, Greece